Cancer gene expression data have the characteristics of high dimensionalities and small samples so it is necessary to perform dimensionality reduction of the data. Traditional linear dimensionality reduction approaches can not find the nonlinear relationship between the data points. In addition, they have bad dimensionality reduction results. Therefore a multiple weights locally linear embedding (LLE) algorithm with improved distance is introduced to perform dimensionality reduction in this study. We adopted an improved distance to calculate the neighbor of each data point in this algorithm, and then we introduced multiple sets of linearly independent local weight vectors for each neighbor, and obtained the embedding results in the low-dimensional space of the high-dimensional data by minimizing the reconstruction error. Experimental result showed that the multiple weights LLE algorithm with improved distance had good dimensionality reduction functions of the cancer gene expression data.
Algorithms ; Gene Expression Regulation, Neoplastic ; Genes, Neoplasm ; Humans ; Neoplasms ; genetics

OBJECTIVE: To screen differentially expressed gene (DEG) related to myelodysplastic syndrome (MDS) based on Gene Expression Omnibus (GEO) database, and explore the core genes and pathogenesis of MDS by analyzing the biological functions and related signaling pathways of DEG. METHODS: The expression profiles of GSE4619, GSE19429, GSE58831 including MDS patients and normal controls were downloaded from GEO database. The gene expression analysis tool (GEO2R) of GEO database was used to screen DEG according to | log FC (fold change) |≥1 and P<0.01. David online database was used to annotate gene ontology function (GO). Metascape online database was used to enrich and analyze differential genes in Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein-protein interaction network (PPI) was constructed by using STRING database. CytoHubba and Mcode plug-ins of Cytoscape were used to analyze the key gene clusters and hub genes. R language was used to diagnose hub genes and draw the ROC curve. GSEA enrichment analysis was performed on GSE19429 according to the expression of LEF1. RESULTS: A total of 74 co-DEG were identified, including 14 up-regulated genes and 60 down regulated genes. GO enrichment analysis indicated that BP of down regulated genes was mainly enriched in the transcription and regulation of RNA polymerase II promoter, negative regulation of cell proliferation, and immune response. CC of down regulated genes was mainly enriched in the nucleus, transcription factor complexes, and adhesion spots. MF was mainly enriched in protein binding, DNA binding, and β-catenin binding. KEGG pathway was enriched in primary immunodeficiency, Hippo signaling pathway, cAMP signaling pathway, transcriptional mis-regulation in cancer and hematopoietic cell lineage. BP of up-regulated genes was mainly enriched in type I interferon signaling pathway and viral response. CC was mainly enriched in cytoplasm. MF was mainly enriched in RNA binding. Ten hub genes and three important gene clusters were screened by STRING database and Cytoscape software. The functions of the three key gene clusters were closely related to immune regulation. ROC analysis showed that the hub genes had a good diagnostic significance for MDS. GSEA analysis indicated that LEF1 may affect the normal function of hematopoietic stem cells by regulating inflammatory reaction, which further revealed the pathogenesis of MDS. CONCLUSION Bioinformatics can effectively screen the core genes and key signaling pathways of MDS, which provides a new strategy for the diagnosis and treatment of MDS.
Computational Biology ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Gene Ontology ; Humans ; Myelodysplastic Syndromes/genetics*

MicroRNA (miRNA) is a class of RNA which has been discovered in recent years and relates with genesis and development of tumors. MiRNA affects the genesis and development of tumors and carries out the function similar to oncogene and antioncogene through regulation of signaling pathway in which target genes involved, thereby the miRNA disregulation plays an important role in oncogenesis. More studies revealed that the miR-17-19 cluster closely correlates with tumorigenesis and has bifunctional effects of oncogene and antioncogene. In this review, the mechanism and function of the miR-17-19 cluster in tumorigenesis are summarized.
Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Genes, Tumor Suppressor ; Humans ; MicroRNAs ; Neoplasms ; genetics ; Oncogenes ; genetics

Hepatocellular carcinoma (HCC) is highly heterogeneous in nature and has been one of the most common cancer types worldwide. To ensure repeatability of identified gene expression patterns and comprehensively annotate the transcriptomes of HCC, we carefully curated 15 public HCC expression datasets that cover around 4000 clinical samples and developed the database HCCDB to serve as a one-stop online resource for exploring HCC gene expression with user-friendly interfaces. The global differential gene expression landscape of HCC was established by analyzing the consistently differentially expressed genes across multiple datasets. Moreover, a 4D metric was proposed to fully characterize the expression pattern of each gene by integrating data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). To facilitate a comprehensive understanding of gene expression patterns in HCC, HCCDB also provides links to third-party databases on drug, proteomics, and literatures, and graphically displays the results from computational analyses, including differential expression analysis, tissue-specific and tumor-specific expression analysis, survival analysis, and co-expression analysis. HCCDB is freely accessible at http://lifeome.net/database/hccdb.
Carcinoma, Hepatocellular ; genetics ; Databases, Genetic ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; Liver Neoplasms ; genetics

Antisense long chain noncoding RNA (lncRNA) is a new class of RNA molecules. In recent years, antisense lncRNA has been found to play an important role in many life activities including tumorigenesis and development. It has become a hot topic in biological research in recent years. Because of the special structure, many antisense lncRNAs have specific expression in tumor tissues and are closely related to the clinical data of the patients. Thus, antisense lncRNA is a potential tumor molecular marker. Further functional studies have shown that lncRNA can participate in gene regulation by means of miRNA sponge and RBP binding to play an important role in tumor cell cycle, apoptosis, angiogenesis, invasion and metastasis. More studies on the mechanisms of antisense lncRNA in cancer are of great theoretical significance in understanding the etiology and pathogenesis of malignant tumors and RNA language. At the same time, antisense lncRNA is a molecular marker or a potential target for the early diagnosis of malignant tumors. The antisense lncRNA may have a broad clinical application prospect in the evaluation of therapeutic effect, prognosis and even gene therapy.
Biomarkers, Tumor ; Gene Expression Regulation ; Gene Expression Regulation, Neoplastic ; Humans ; MicroRNAs ; genetics ; Neoplasms ; genetics ; RNA, Long Noncoding ; genetics

OBJECTIVETo study the differently expressed genes of oral squamous cell carcinoma (OSCC) tissue.

METHODSGene expression datasets related to oral squamous cell carcinoma in the gene expression omnibus (gene expression omnibus, GEO) repository were retrieved. Datasets were merged by normalization.Significantly expressed genes were obtained by statistical methods, and genes' functions, interactions, signaling pathways were analyzed accordingly.

RESULTSIn GEO, there were 1 125 records related to OSCC, and four of them were selected and merged to a super array data, within the super array data, 233 genes were significantly expressed (P < 0.05) , and the top 100 significantly expressed genes were selected as signature genes.Signature genes were more related to cell surface or cell-cell interactive activities. Clusters of interactive signature genes and the related signaling pathways were related with mitosis process.

CONCLUSIONSOSCC signature genes and the corresponding signaling pathways will provide not only an important clue for further research of the disease, but also reference for diagnosis and treatment.

Carcinoma, Squamous Cell ; genetics ; Gene Expression ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; Mouth Neoplasms ; genetics ; Signal Transduction

OBJECTIVETo investigate telomerase activity and expression of hTR and hTERT in human neuroepithelial tumors for exploring new strategy for clinical diagnosis and treatment.

METHODSTelomerase activity was detected by modified TRAP method and the expression of hTR and hTERT was measured by RT-PCR method in 65 human neuroepithelial tumors, respectively.

RESULTSThe positive rates of telomerase and hTERT were 61.54% and 70.77% respectively in human neuroepithelial tumors, and the positive rate and their level of expression were correlated with the degree of malignancy of tumors positively.

CONCLUSIONSTelomerase activity and hTERT are significantly correlated with the degree of malignancyin human neuroepithelial tumors. hTERT may play a key role in the regulation of telomerase activity.

DNA-Binding Proteins ; Gene Expression Regulation, Enzymologic ; Gene Expression Regulation, Neoplastic ; Humans ; Neoplasms, Neuroepithelial ; enzymology ; genetics ; Telomerase ; biosynthesis ; genetics ; metabolism

OBJECTIVEThis article aims to review recent studies on the biological characteristics of long non-coding RNAs (lncRNAs), transcription regulation by lncRNAs, and the results of recent studies on the mechanism of action of lncRNAs in tumor development.

DATA SOURCESThe data cited in this review were mainly obtained from the articles listed in PubMed and HighWire that were published from January 2002 to June 2010. The search terms were "long non-coding RNA", "gene regulation", and "tumor".

STUDY SELECTIONThe mechanism of lncRNAs in gene expression regulation, and tumors concerned with lncRNAs and the role of lncRNAs in oncogenesis.

RESULTSlncRNAs play an important role in transcription regulation by controlling chromatin remodeling, transcriptional control, and post-transcriptional controlling. lncRNAs are involved in many kinds of tumors and play key roles as both suppressing and promoting factors.

CONCLUSIONlncRNAs could perfectly regulate the balance of gene expression system and play important roles in oncogenic cellular transformation.

Animals ; Cell Transformation, Neoplastic ; genetics ; Gene Expression Regulation ; genetics ; physiology ; Humans ; Neoplasms ; genetics ; RNA, Untranslated ; genetics

OBJECTIVE: To screen potential pan-cancer biomarkers based on The Cancer Genome Atlas (TCGA) database, and to provide help for the diagnosis and prognosis assessment of a variety of cancers. METHODS: "GDC Data Transfer Tool" and "GDCRNATools" packages were used to obtain TCGA database. After data sorting, a total of 13 cancers were selected for further analysis. False disco-very rate (FDR) < 0.05 and fold change (FC) >1.5 were used as the differential expression criteria to screen genes and miRNAs that were up- or down-regulated in all the 13 cancers. In the receiver operating characteristic curve (ROC curve), the area under the curve (AUC), the best cut-off value and the corresponding sensitivity and specificity were used to reflect diagnostic significance. The Kaplan-Meier method was used to calculate the survival probability and then the log-rank test was performed. Hazard ratio (HR) was calculated to reflect prognostic evaluation significance. DAVID tool were used to perform GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis for differentially expressed genes. STRING and TargetScan tools were used to analyze the regulatory network of differentially expressed genes and miRNAs. RESULTS: A total of 48 genes and 2 miRNAs were differentially expressed in all the 13 cancers. Among them, 25 genes were up-regulated, 23 genes and 2 miRNAs were down-regulated. Most differentially expressed genes and miRNAs had good ability to distinguish between the cases and controls, with AUC, sensitivity and specificity up to 0.8-0.9. Survival analysis results show that differentially expressed genes and miRNAs were significantly associated with patient survival in a variety of cancers. Most up-regulated genes were risk factors for patient survival (HR>1), while most down-regulated genes were protective factors for patient survival (0 < HR < 1). The enrichment analysis of GO and KEGG showed that the differentially expressed genes were mostly enriched in biological events related to cell proliferation. In the regulatory network analysis, a total of 13 differentially expressed genes and 2 differentially expressed miRNAs had regulatory and interaction relationships. CONCLUSION The 48 genes and 2 miRNAs that were differentially expressed in 13 cancers may serve as potential pan-cancer biomarkers, providing help for the diagnosis and prognosis evaluation of a variety of cancers, and providing clues for the development of broad-spectrum tumor therapeutic targets.
Biomarkers, Tumor/genetics* ; Early Detection of Cancer ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; MicroRNAs/genetics* ; Neoplasms/genetics* ; Prognosis

OBJECTIVEThis review aimed to update the progress of microRNA (miRNA) in early detection of ovarian cancer. We discussed the current clinical diagnosis methods and biomarkers of ovarian cancer, especially the methods of miRNA in early detection of ovarian cancer.

DATA SOURCESWe collected all relevant studies about miRNA and ovarian cancer in PubMed and CNKI from 1995 to 2015.

STUDY SELECTIONWe included all relevant studies concerning miRNA in early detection of ovarian cancer, and excluded the duplicated articles.

RESULTSmiRNAs play a key role in various biological processes of ovarian cancer, such as development, proliferation, differentiation, apoptosis and metastasis, and these phenomena appear in the early-stage. Therefore, miRNA can be used as a new biomarker for early diagnosis of ovarian cancer, intervention on miRNA expression of known target genes, and potential target genes can achieve the effect of early prevention. With the development of nanoscience and technology, analysis methods of miRNA are also quickly developed, which may provide better characterization of early detection of ovarian cancer.

CONCLUSIONSIn the near future, miRNA therapy could be a powerful tool for ovarian cancer prevention and treatment, and combining with the new analysis technology and new nanomaterials, point-of-care tests for miRNA with high throughput, high sensitivity, and strong specificity are developed to achieve the application of diagnostic kits in screening of early ovarian cancer.

Early Detection of Cancer ; methods ; Female ; Gene Expression Regulation, Neoplastic ; genetics ; Humans ; MicroRNAs ; genetics ; Ovarian Neoplasms ; genetics